Dr. Maneesha V. Ramesh is the Director & Professor at Amrita Center for Wireless Networks and Applications (AWNA) and Dean for Amrita Center for International Programs, Amrita Vishwa Vidyapeetham

Dr. Maneesha V. Ramesh pursued her Ph. D. in Computer Science from Amrita Vishwa Vidyapeetham and authored a research thesis titled Wireless Sensor Network to Detect Rainfall Induced Landslides. Her research work was instrumental in deploying the first ever Wireless Sensor Network system capable of issuing landslide warning. She has received U.S. Patent US 13/168,3572014. for this work, "Network based system for predicting landslides and providing early warnings". She has an M. B. A. in Systems Management and Financial Management from Amrita University. She completed her B. Tech. in Production Engineering from Kerala University.

Dr. Maneesha V. Ramesh is the Dean of International Programs. She heads all the activities of Amrita Center for International Programs (ACIP). The Center has been incharge of developing collaborative initiatives between Amrita Vishwa Vidyapeetham and other International Universities. The main work includes developing MoU with international universities for faculty and student exchange programs, dual degree programs, research collaborations etc. As of now Amrita has signed 153 MoU's since 2005.

Dr. Maneesha had given distinguished lectures in different reputed Universities during visits at International Universities. Since 2007 she had published more than 94 publications, including three best paper awards. Dr. Maneesha was awarded the prestigious Young Faculty Research Fellowship under Visvesvaraya PhD scheme for Electronics and IT for the year 2015-16 from The Department of Electronics & Information Technology, Government of India. She has received the national award, NABARD award for her work on landslide monitoring and early warning system. She is the Editor of Ad Hoc Networks Journal published by Elsevier.

Qualification

Doctorate (June 2009)

Ph. D. in Computer Science from Amrita Vishwa Vidyapeetham
Thesis topic : Wireless Sensor Network to detect rainfall induced landslides
(The research work was instrumental in deploying world’s first ever Wireless Sensor Network system capable of issuing landslide warning. One such landslide warning was issued on July 22, 2009 during the torrential rainfall season.)

Awarded the 'Young Faculty Research Fellowship' under the Visveswaraya PhD Scheme for Electronics and IT of DeitY for the year 2015-16.

CREATE UNAOC Challenge Award : 'Sanskar', an interactive Android app, developed by Dr. Maneesha was shortlisted among the top five finalist applications in the 2012 Create UNAOC Challenge, an international competition for app developers that sought to introduce new avenues for intercultural dialogue.

Best Paper Awarded for the paper titled ''Wireless Sensor Network Security: Real-Time Detection and Prevention of Attacks" in the 4th International Conference on Advanced Computer Control (ICACC 2012) 2012, Nov. 7-8, 2012 held at Shanghai, China.

WINSOC has been featured in the newspaper, “The Telegraph”, which is one of the major Indian newspapers. It has been published in its “know HOW” section titled as “Early Warning System”. The online version can be accessed through the link.

Invited Lectures at Conferences & Workshops

Workshop on University Networks for Education and Research in Disaster RiskManagement atBangkok, Thailand : December, 2009

IEEE workshop on Humanitarian Technology Challenges of the 21st Century Trivandrum, Kerala, India : February 2010

Workshop on geo-spatial technologies organized by Indian Institute of Technology, Mumbai : December 2009.

The National Workshop “ UbiComp India 2008”

The Workshop on “Wireless Sensor Networks: Technology and Roadmap”, sponsored by Government of India’s Ministry of Communication and Information Technology (MCIT), and Department of Information Technology (DIT), at Indian Institute on Technology, Mumbai, India.

“National Symposium on Mathematical Methods and Applications on December 22, 2005 at IIT Chennai. A paper on "Medical Image Encryption using Wavelets" was presented at the symposium.

Dr. Maneesha V. Ramesh had delivered a talk on 'Credit Transfer and Transnational Education' at International Meet being organized by the Kerala State Higher Education Council from January 3 -5, 2014.

International Institute for Geo-Information Science and Earth Observation, Netherlands

University of Paderborn, Germany

University of Mannheim, Germany

University of Montpellier 2, France

Universitat Politecnica De Catalunya (UPC), Spain

Universitat Pompeu Fabra(UPF), Spain

Other Conferences & Workshops

Dr. Maneesha V.Ramesh and Dr. Maarten van Steen, Scientific Director of CTIT, University of Twente spoke on the topic Wireless Communication for Disaster Management during the one day conference "Technology for Sustainable Development" on July 8, 2015 at United Nations, New York that was jointly hosted by United Nations Academic Impact and Amrita Vishwa Vidyapeetham

A novel cost-effective network architecture for providing Internet connectivity to marine fishermen has been successfully prototyped by our research center. A pilot deployment is in progress in a coastal Indian village. This will improve the quality of life of the financially constrained marine fishermen who spend 5-7 days offshore on average for a single fishing trip; it will also help in their safety and security. The architecture employs multiple long range Wi-Fi (LR Wi-Fi) based infrastructure networks stitched together as backhaul. The access network consists of Ethernet and Wi-Fi mesh. The fishermen connect to the on board Wi-Fi access point cum router using their smart phones and are able to use all the apps and services on their smart phone. While the primary infrastructure network uses onshore base stations, the secondary infrastructure networks use boats as mobile base stations. Three field trials were conducted over the ocean using one onshore base station and two mid-sized boats known as trawlers. The performance of both primary and secondary infrastructure networks was assessed during these field trials. This paper describes the impressive results obtained in assessing the performance of the secondary infrastructure network.

Energy consumption in official buildings contributes to 42% of total energy generation in India. The key features in commercial buildings are usage of high energy consuming devices, long duration of usage of electrical equipments, large population density and large equipment density compared with the floor area usage in houses. Hence this problem has motivated to perform research on energy management in official buildings. The individuals in these buildings mostly have unique authority on most of the equipments they handle, and they have their own comfort level requirement based on the context and the equipment availability. Therefore, to devise an effective energy management solution it is required to consider personal requirements with highest priority than the community requirements. Hence in this research work we design and develop systems &amp; solutions needed for Personalized Energy Management (PEM). Our proposed system is developed to capture the spatio-temporal data of context and electrical usage pattern for each individual with bare minimum sensors. To address this challenge, we proposed a smart positioning system (SPS) for personalized energy management. In SPS, we have developed an Real time Smart Positioning System (RSPS) algorithm for integrating electrical map and sensing coverage of electrical appliances inside a building to position the individual in real-time with respect to each of the electrical appliances. Using SPS, the current position of an individual inside the building is determined along with the position of nearby electrical appliances to automate the appliance usage. This is performed using the proposed RSPS algorithm where real-time mapping of electrical map, sensing coverage of nearby equipments, signal strength, and pattern of individual requirements are used to control usage of equipments related to individual's choice. Experimental analysis of the RSPS algorithm on our prototype has been performed and the results showed that it requi- es a minimum of 2 coverage and it is not required to have 3 coverage as in other localization algorithms. Under the above condition of 2 coverage this algorithm was able to achieve an accuracy of 90%.

Using wireless networks to connect and communicate between geological sensors is a more scalable and suitable way for designing landslide monitoring and warning system for larger areas spanning many acres. Added to this, if the system has the capability to function in solar power, then it becomes autonomous system with self-organizing and self-healing networks. But high terrain, steep slopes, dense vegetation and lack of light during monsoon season to generate solar power pose serious challenges to develop such an autonomous system with good wireless coverage. This paper is about efforts to design, develop and deploy one such landslide warning system in eastern Himalayas. Pilot deployment is already in place and full deployment is under progress.

Nowadays wireless sensor networks are implemented in a variety of fields to obtain real-time measurements. These networks are comprised of small, low cost devices called wireless sensor nodes (WSN). There are different types of wireless sensor nodes available in the market. Based on the requirements, wireless sensor nodes can be selected for each application. Power consumption is a major aspect in developing wireless sensor applications. In this paper, analysis of power consumption in different sensor nodes is conducted based on algorithms with different complexities. The experimental analysis results show that at a particular input current limit, Waspmote consumes 15% less power than MICAz mote in the case of O (1), 11.04% less in the case of O (n), 7.6% less in the case of O (n2), 3.9% less in case of O (log n) and 18.06% less in case of O (m+n)complex algorithms.

Remote health monitoring and delivery through mobile devices and wireless networks offers unique challenges related to performance, reliability, data size, power management, and analytical complexity. We present a multi-layered architecture that matches communication performance to medical importance of data being monitored. The priority of vital data and the context of sensing are used to select the communication medium and the power management policies. Further smartness is introduced into data summarization by employing a severity level quantizer, followed by a consensus abnormality motif discovery and an alert mechanism that prioritizes doctors' consultative time. We also present our successful implementation of the above multi-layered architecture in a system developed to remotely monitor cardiac patients.

S. Shaji, Dr. Maneesha V. Ramesh, and Menon, V. N., “Real-time processing and analysis for activity classification to enhance wearable wireless ecg”, in Proceedings of the Second International Conference on Computer and Communication Technologies, 2016.[Abstract]

Health care facilities of our rural India are in a state of utter indigence. Over three-fifths of those who live in rural areas have to travel more than 5 km to reach a hospital and the health care services is becoming out of reach for the economically backward society of India. Currently, as the rural community experiences about 22.9% of death due to heart diseases [1], there is a need to improve the remote ECG monitoring devices to cater the needs of rural India. The existing wearable ECG devices experience several issues to accurately detect the type of heart diseases due to the presence of motion artifacts, and to warn the doctor during critical conditions. Hence, even though wearable devices are finding their place in today’s healthcare systems, the above mentioned issues discourages a doctor in depending upon it. So to enhance the existing wearable ECG device, a context aware system was designed to collect the BMA (Body Movement Activity). In this research work an innovative BMA classifier has been designed to classify the physical activities of users, from the real-time data received from context aware device. The test results of the BMA classifier integrated with the complete system shows that algorithm developed in this work is capable of classifying the user activity such as walking, jogging, sitting, standing, upstairs, downstairs, and lying down, with an accuracy of 96.66%.

Smart distribution grids will be a combination of existing electrical networks controlled by distributed software applications communicating via communication networks. This means that not only the reliability of individual technologies are crucial, but the interoperability is also pivotal for the robustness of the smart distribution network. These individual research areas (electrical network, distributed software controller and communication network) have their corresponding fault handling strategies and several proven solutions exist to ensure reliability. The objective of our work is to integrate the solutions from these individual technologies. We focus on the interoperability and integration of individual fault handling strategies that are essential for improving the reliability and robustness of the overall smart distribution network. In this paper, we describe our approach in creating a single solution from the existing individual strategies to create a robust smart distribution network. We also present the details of the demonstrator design that is being built to evaluate our approach.

In most of the real world wireless sensor network deployments, the energy utilization is a critical factor as the nodes are battery powered. In most of the real-world deployments it is observed that the sensing subsystem consumes higher power. In order to extend the lifetime of such systems it is required to reduce the sensing energy than communication energy. We have deployed a system for monitoring Landslides in India consists of 150 geo-physical sensors and used solar panels to power these sensor nodes. The decision making in favor of Landslide occurrence is based on the maximum values obtained from the high priority sensors. As this maximum value is not frequently changing in the deployment, locating the sensor node with maximum value allows us to switch off the other sensors for a predetermined period of time. This work proposes an optimal balanced network topology for delay minimization by parallelizing data aggregation operation in each sub-network. The sensor node switch off schemes on the top of delay minimized topology enables the optimal utilization of the available solar power. The analysis of these mechanisms shows that, more number of nodes can be powered with the available source of energy and can increase the network life time.

Marine fishermen risk their lives when they go as far as 120 km from the shore on a fishing trip lasting 5-7 days. They are completely cut off from the mainland. Cellular coverage exists only up to 12-15 km from the shore. In emergency situations, the fishermen have no way to call for help. Even under normal conditions, prolonged isolation from their family and friends causes mental depression. Since the marine fishermen are not economically well off especially in the developing countries, there has not been much commercial interest in addressing this problem. It is not seen as a profitable business proposition. However, addressing this problem will benefit the marine fishermen community immensely. Our center conducted interviews with several fishermen to understand this problem and came up with a cost-effective solution. The solution enables the fishermen to use the smart phones which they own already to get internet at sea using Wi-Fi. The Access Point (AP) on the boat connects over Ethernet to an onboard gateway to long range Wi-Fi backhaul network. The onshore base station is installed on a tower at a height of 50-60 m. Boats are also used as mobile base stations to extend the range of the network. This solution, when tested over the Arabian Sea, provided a range of 40+ km in the first hop and 20+ km every subsequent hop. This network can be operated on a cooperative community basis by the fishermen community at reasonable per capita CAPEX and OPEX. A pilot deployment is in progress in a coastal village community in Kerala, India, to gain operational experience.

Water scarcity has been a major thrusting issue in rural India, warrantinga high demand to design and implement different water distribution networks for easy and efficient use of existing water sources. Both macro and micro level systems exist of which, macro level water distribution networks have higher capital and maintenance costs. This is due to its size and the remote beneficiaries to which it caters. This paper describes the design of one such water distribution system in two rural villages in India whose design considerations includes the local community needs, availability of labor, local resources, climate, cost, and time for implementation. This paper also compares the micro and macro water distribution network's impact on sustainability. Sustainability is defined in terms of water wastage, usage rate, source capacity, total network length, cost of deployment, source recharge, and the network leakage rate. The paper discusses the water distribution projectscompletedin a village in Orissa and in a village in Rajasthan (two states in India) where all households were given 24/7 access to clean and safe drinking water for more than a year. The paper also draws insights on the socio-economic impact of the project carried out in these two states.

Landslides are one of the major natural disasters and an early detection of landslide can be achieved by identifying the landslide triggering vibrations recorded using a geophone network. The major research challenges in this effort are network energy consumption, noise removal and development of a wireless network for transmitting the captured signals. This paper presents design and testing of a wireless smart geophone network with enhanced signal processing capability at the site for recording and analyzing geophone signals. The system has the capability to detect landslide induced signals and remove different types of noises produced by footsteps, vehicular movement, rainfall, and stream flow, and transmit the event data to a local processor. For this purpose, a simple and cost effective Arduino based data acquisition system with geophone inputs is developed. This system helps in reducing the system energy conception and is highly reliable, low cost compared to other traditional systems. This paper mainly focuses on the hardware design of sensor system and algorithms for identifying the characteristics of geophone signals for detecting landslide induced seismic signals. The characteristics of geophone signals for different seismic events recorded by the system are also provided.

This paper presents a remote triggered wireless sensor network (WSN) testbed used to facilitate multi-user remote access to the WSN experiments for virtual learning of wireless sensor network concepts. This testbed provides multiset, multi-group of WSN experimental setup that is capable to provide opportunity to perform remote code editing using over the air programming mechanism. This testbed also provides an intuitive web-based interface to the registered users for running the experiments, accessing and editing the source code of the experiment from anywhere in the world by means of internet. This remote triggering mechanism offers the user a flexible environment for the experimentation. An experimentation setup of 150 wireless sensor nodes are developed to suit the design of both indoor and outdoor experiments. The outdoor lab setup allows the users to learn the wireless propagational effects in the real environment. The WSN indoor lab setup comprises of nine sensor network experiments which allows the users to learn the WSN concepts such as configuring a WSN, clustering mechanisms, time synchronization mechanisms and experience the practical implementation in real time. This test bed offers the researchers and students an opportunity to trigger their inquisitiveness by providing the access to remote equipments and materials needed for the experimentation, shared via virtual manner wherein the experiment conduction and output observation can be performed online through an effective visualization tool.

In this paper, we present a real time remote triggered laboratory which has multi-set, multi-group of wireless sensor network experimental setup which is envisioned to provide a practical experience of designing and implementing wireless sensor networks’ algorithms in both indoor and outdoor conditions. The architecture provides a remote code editing mechanism using deluge protocol that offers the user a flexible environment for the experimentation. Central and local authentication agents serve a two level security mechanism which makes the system robust to security threats. The lab is accessible for all the students in the world through internet and it will provide an intuitive web-based interface, where registered users can access the code and do code editing.

Theft of electricity amounts to 1.5% GDP, of most of the developing nations like India. Hence there is a great need to detect power thefts in developing nations. In this paper, we have proposed a wireless network based infrastructure for power theft detection which caters to other functional requirements of the microgrid such as renewable energy integration, automatic meter reading etc. Algorithm for power theft detection (PTDA) which is proposed in this paper, works in the distributed intelligent devices of the microgrid infrastructure for power theft detection. The coordinated action of intelligent devices with PTDA in the microgrid infrastructure enables not only the detection of power theft, but the localization of power theft in the micro-grid. PTDA increases the 1) cost of communication 2) energy consumption of intelligent devices 3) packet latency, if any critical data is piggy backed with power theft data in micro-grid. To solve these issues, we have proposed EPTDNA (Efficient Power Theft Data Networking Algorithm) which uses the frequency of power theft detection and average power draw for power theft, for the efficient routing of power theft. The performance analysis and results given in this paper shows how EPTDNA solves the major issues with PTDA.

Several challenges exist in developing smart buildings such as the development of context aware algorithms and real-time control systems, the integration of numerous sensors to detect various parameters, integration changes in the existing electrical infrastructure, and high cost of deployment. Another major challenge is to optimize the energy usage in smart buildings without compromising the comfort level of individuals. However, the success of this task requires in depth knowledge of the individual and group behaviour inside the smart building. To solve the aforementioned challenges, we have designed and developed a Smart Personalised System for Energy Management (SPSE), a low cost context aware system integrated with personalized and collaborative learning capabilities to understand the real-time behaviour of individuals in a building for optimizing the energy usage in the building. The context aware system constitutes a wearable device and a wireless switchboard that can continuously monitor several functions such as the real-time monitoring and localization of the presence of the individual, real-time monitoring and detection of the usage of switch board and equipment, and their time of usage by each individual. Using the continuous data collected from the context aware system, personalized and group algorithms can be developed for optimizing the energy usage with minimum sensors. In this work, the context aware system was tested extensively for module performance and for complete integrated device performance. The study found the proposed system provides the opportunity to collect data necessary for developing a personalized system for smart buildings with minimum sensors.

Over the past decade, experimentation for wireless sensor network (WSN) has been widely used to enrich the learning experience of educators and learners. Our remote triggered WSN laboratory is a multi-set, multi-group, WSN experimental setup that provides an intuitive web-based interface to carry out remote experimentation as well as code editing by registered users. This paper presents a multi-level time based scheduling algorithm for our lab which provides optimum utilization, performance and service. Our WSN testbed consists of more than 150 sensor nodes deployed in indoor and outdoor environment. Energy efficiency and delay optimization of WSN testbed are ensured in the design which employs TDMA and state transition schemes. We have implemented and tested two approaches for energy efficiency namely an on demand scheduling and a TDMA based approach which incorporates state transition and CDMA. The performance evaluation result shows that 78% power consumption has been reduced in second approach compared to first. The paper details the implementation of energy efficiency with dynamic scheduling for our real-time remote triggered WSN.

Our AMRITA remote triggered lab (RT Lab) for wireless sensor networks (WSN) offer the students and researchers, an easy, efficient, interactive and user friendly environment to trigger their inquisitiveness by providing them with the sensors, equipments, hardwares and study materials for conducting the lab experiments. RT Lab offers a web-based e-learning platform for the registered users to perform experimentation and coding remotely based on the provided study materials which are shared to them virtually. The users can learn nesC programming language and conduct the coding by means of the code editing interface. The sensor nodes in the WSN testbed, deployed in indoor and outdoor environment, undergoes remote reconfiguration and the sensor data's are collected by the WSN gateway. The users can observe the experimentation result such as the plotted sensor data and physical representation of the sensor network along with the remote video through the visualization tool. The paper details the design and implementation of remote code editing platform for RT Lab.

Cardiovascular diseases in rural developing countries take a large toll of human lives, due to inadequate quality health care facilities and their limited reach to the patients. The burgeoning population of developing nations make the lin- ear organic scaling of health care facilities impractical to cater the diverse rural geography. Hence it is imperative to scale the health care facilities through wireless communi- cation technologies in an aordable manner. Timely anal- ysis of ECG data is critical for early diagnosis and treat- ment of several cardiovascular diseases. With this aim, a wearable wireless ECG monitoring framework, named as Amrita-Spandanam was designed. This framework consist of a patient wearable device and a patient smart phone with Amrita-Spandanam application, enabling a doctor/hospital to monitor the remote patient through his internet con- nected mobile phone or web browser. The framework does the post analysis of the ECG signal using a backend server to disseminate warnings to the doctor and the patient. Sev- eral de-noising algorithms were applied to the acquired ECG signal prior to this post analysis. The framework was imple- mented successfully enabling real time remote monitoring of the cardiac patients in rural villages.

Wearable ECG monitoring is becoming a convenient way for patients as well as doctors, in tracking and diagnosing heart diseases among large population in rural areas. Wear- able ECG devices along with the smartphones are used to capture and transmit ECG data to hospitals where medi- cal practitioners diagnose and make suitable interventions. ECG electrode cable misplacement poses signicant chal- lenge when untrained population is the end-user. We present a real-time lead misplacement detection system for Mason- Likar lead conguration to provide immediate feedback to patients. It reduces chances of pseudo-disease diagnosis as well as the need for technicians to conrm the validity and quality of captured ECG data. The eld test results show that six dierent Mason-Likar electrode misplacement can be detected and dierentiated from a normal one with a condence value p=0.05.

One of the major problems power grids system face today is the inability to continuously deliver power at the consumer side. The main reason for this is the occurrence of faults and its long term persistence within the system. This persistence of faults causes the cascading failure of the system, thereby adversely affecting the connected loads. Traditional methods of fault isolation cause the shutdown of power to a large area to maintain the system stability. Today, localization of faults and its isolation is doing manually. Therefore, a localized fault recovery mechanism is very essential to maintain the system’s stability after the occurrence of a fault. In this paper, we have developed fast fault detection and isolation mechanism for single phase to neutral line fault in a three phase islanded micro grid scenario. The fault detection and isolation during the islanded operation mode of a micro grid is very critical, since bidirectional power flow is present. The fault detection mechanism we developed can detect and isolate the fault within a few milliseconds and localize the fault within a two second delay for both in single and bi-directional power flow scenarios. The proposed system is capable of locating the exact faulted segment with the aid of the communication network integrated into the power grid. The implemented system was tested with different ranges of fault current and the analysis showed that the proposed system could localize the fault with less than a two second delay.

Most of the critical challenges seen in the past decades have impacted citizens in a global way. Given shrinking resources, educationists find preparing students for the global market place a formidable challenge. Hence exposing students to multi-lateral educational initiatives are critical to their growth, understanding and future contributions. This paper focuses on European Union’s Erasmus Mundus programs, involving academic cooperation amongst international universities in engineering programs. A phased undergraduate engineering program with multiple specializations is analyzed within this context. Based on their performance at the end of first phase, selected students were provided opportunities using scholarship to pursue completion of their degree requirements at various European universities. This paper will elaborate the impact of differing pedagogical interventions, language and cultural differences amongst these countries on students in diverse engineering disciplines. The data presented is based on on the feedback analysis from Eramus Mundus students (N=121) that underwent the mobility programs. The findings have given important insights into the structure of the initiative and implications for academia and education policy makers for internationalizing engineering education. These included considering digital interventions such as MOOCs (Massive Open Online Courses) and Virtual Laboratory (VL) initiatives for systemic reorganization of engineering education.

Urinary Incontinence is the most common health problem in old people, autistic kids and diabetic patients with significant social and economic impact in the quality of life. According to WHO, 20 million people are affected by Urinary Incontinence. This paper proposes an integrated architecture to continuously monitor the patients' bladder and remotely trigger the wireless artificial sphincter system using wireless power transfer in real time. After analysis, a few Ionic Electro Active Polymers (EAP) were selected to physically control the urethra. Possible designs using EAP polymer for urethra control are elaborated in this paper. This paper analyzes the major challenges of wireless power and data transfer and its impact on the design of the complete system. The proposed system provides a solution to continuously monitor the bladder and send alert messages to the control system that's on the patient's body. On receiving these alerts, patients' will remotely trigger the artificial sphincter control system to release the urine from their bladder. Thus the patients or caregivers can monitor the pressure inside their bladder and control urinal flow remotely by opening and closing the ionic EAP clip from outside. The system design has been simulated and tested with its different parameters and its results are discussed in this paper.

The high computational complexity of text classification is a significant problem with the growing surge in text data. An effective but computationally expensive classification is the k-nearest-neighbor (kNN) algorithm. Principal Component Analysis (PCA) has commonly been used as a preprocessing phase to reduce the dimensionality followed by kNN. However, though the dimensionality is reduced, the algorithm requires all the vectors in the projected space to perform the kNN. We propose a new hybrid algorithm that uses PCA &amp; kNN but performs kNN with a small set of neighbors instead of the complete data vectors in the projected space, thus reducing the computational complexity. An added advantage in our method is that we are able to get effective classification using a relatively smaller number of principal components. New text for classification is projected into the lower dimensional space and kNN is performed only with the neighbors in each axis based on the principal that vectors that are closer in the original space are closer in the projected space and also along the projected components. Our findings with the standard benchmark dataset Reuters show that the proposed model significantly outperforms kNN and the standard PCA-kNN hybrid algorithms while maintaining similar classification accuracy.

The deployment of a wireless sensor network for real-time monitoring applications encounters numerous challenges. In a typical outdoor scenario the propagation of the radio signal can be affected by several factors like the rainfall, foliage, path loss effect and fading effect. These factors can confront dynamic changes in link quality which will affect the packet delivery rates and can result in the failure of the system. This paper presents an optimized frequency selection for any wireless sensor networks which can enhance the packet delivery ratio at any worst environmental scenarios through a simulated framework in QualNet 5.0.2.

Statistics show that the figure of new cancer cases and deaths reported each year are increasing considerably. The current situation demands an efficient targeted drug delivery system that enables localized drug administration which can be externally controlled. This paper proposes a remotely triggered targeted drug delivery system that is capable of providing drugs to multiple patients in a periodic basis and works according to the instructions transmitted from the external transmitter module. We present the characteristics and challenges in the propagation of Radio Frequency (RF) signals through different body tissues from the perspective of targeted drug delivery system so that the analysis can lead to the selection of optimum frequency needed for in-body communication. This paper focuses on the design of an implantable drug delivery system, based on the optimum frequency obtained from the simulation results.

Sensor nodes in wireless sensor network are powered by batteries and thus the utilization of effective energy management techniques becomes one of the most important challenges in realistic design of WSN. This paper deals with an optimal energy management scheme in Landslide detection system deployed in Kerala. Based on the meteorological, hydrological and soil parameters, sensors will be dynamically prioritized, scheduled and selects appropriate sensors for event handling. The results of this research work shows that the life time of the network has been improved due to the implementation of this adaptive energy management scheme.

Electricity usage is increasing day by day due to the changing life style of home user and an increase in appliances in the home area network. Our proposed home energy management system for home users will monitor, manage and control the usage of home appliances, by reducing the monthly electricity bill. The proposed wireless architecture consists of an appliance control device called Wireless Enabled Electricity Manager (WEEMAN) installed next to a switch board or every device/appliance in a room. The central node called smart meter runs an algorithm called Availability Based Energy Management algorithm. This algorithm learns about the previous usage patterns of the appliances, collects real time power consumption of appliances from WEEMAN to generate efficient energy load patterns. The highpoint of the algorithm is that it gives an option for the user to set their monthly current bill and pro-actively control the operation of all the appliances according to the amount. We have developed a hardware test bed consisting of WEEMAN connected to some selected appliances and a smart meter to control every WEEMAN.

Cardiovascular diseases (CVD) are one of the leading causes of death in rural India. Every year more than 3 million Indian citizens die from CVD [1]. The proposed Wearable Wireless Cardiac Monitoring (WiCard) system, aims to bring home state-of-the-art health care for people living in rural Indian villages, where thousands of death occur each year due to lack of experts and facilities. The architecture involves remote monitoring of the ECG by specialized health professionals via a heterogeneous wireless network. This paper discusses the development of a six lead custom hardware for transmitting data to a Smartphone or a compatible device via a Bluetooth. The data received by the mobile devices will be further processed and transmitted to a central repository located in a specialized hospital. The main disadvantage of wearable cardiac monitoring system is the introduction of Motion Induced Artifacts (MIA), which could mimic a cardiac event. A context aware architecture is proposed here to relate physical activity and physiological signals of the user, with the help of accelerometer sensors. The portion of ECG where the MIA has detected will be tagged and sent to the central repository. Classifications of physical movements are done using statistics based classifiers, which are computationally low cost. The results show that the developed algorithm is capable of classifying the user activity with an accuracy of 94%. The developed hardware achieved a power reduction of 10 %.

There is a lack of timely access to necessary healthcare in remote areas, especially in India. This paper addresses the availability of quality healthcare, by introducing wireless technology to monitor patients, in remote areas. A reliable system to continuously monitor the patients in the remote areas has been developed, this software suite consists of two mobile software platforms. The first mobile software platform uses wearable wireless sensors to collect a Patient's ECG and Blood Pressure based on the patient's health condition. This sensed data is transmitted to the Patient's mobile phone where the first level of analysis is performed and an emergency warning may be indicated. If the patient's parameters are at a certain level a message is sent immediately to the Health Professional's mobile phone. The health data is also transmitted it to a central server for storage and further processing. This database can be of great value to health researchers. The second mobile software platform enables health professionals to view patient's health reports on their mobile phones from the central database. The health professional can also assign the risk levels of each patient, from the health professional's mobile phone. Both platforms communicate with the central database using a web server. This research also considers power optimization in the patient's mobile.

Disasters aroused due to dynamic movement of large, uncontrollable crowds are ever increasing. The inherent real-time dynamics of crowd need to be tightly monitored and alerted to avoid such disasters. Most of the existing crowd monitoring systems is difficult to deploy, maintain, and dependent on single component failure. This research work proposes novel network architecture based on the key technologies of wireless sensor network and mobile computing for the effective prediction of causes of crowd disaster particularly stampedes in the crowd and thereby alerting the crowd controlling station to take appropriate actions in time. In the current implemented version of the proposed architecture, the smart phones act as wireless sensor nodes to estimate the probability of occurrence of stampede using data fusion and analysis of embedded sensors such as tri-axial accelerometers, gyroscopes, GPS, light sensors etc. The implementation of the proposed architecture in smart phones provides light weight, easy to deploy, context aware wireless services for effective crowd disaster mitigation.

The patients in rural areas lose their lives due to the unavailability of proper healthcare at the right time. This research work aims to develop a system suitable for continuous and real-time monitoring of rural patients to enhance healthcare facilities. The proposed system integrates existing and freely available mobile technology with wearable wireless sensors for patient monitoring. This research work has designed and developed a mobile software platform for continuous and real-time monitoring of rural patients. The prototype platform has been enhanced by integrating power optimizing and risk based data collection and transmitting methodologies. The system also provides an emergency warning message to the doctor's mobile phone. This proposed system collects the patient's health related sensor details in mobile phone, performs a first level analysis of the collected data, and transmits it to a central server for further processing. The system also enables the doctor to receive and view patient's ECG reports to a mobile phone. This paper introduces a dynamic algorithm to increase the battery life of a health monitoring mobile phone.

Wireless Sensor Networks (WSNs) consist of distributed autonomous devices which sense the environmental or physical conditions cooperatively and pass the information through the network to a base station. Sensor Localization is a fundamental challenge in WSN. Location information of the node is critically important to detect an event or to route the packet via the network. In this paper localization is modeled as a multi dimensional optimization problem. This problem is solved using bio inspired algorithms, because of their quick convergence to quality solutions. Distributive localization is addressed using Particle Swarm Optimization (PSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). The performances of both algorithms are studied. The accuracy of both algorithms is analyzed using parameters such as number of nodes localized, computational time and localization error. Comparison of both the results is presented. A simulation was conducted for 100 target nodes and 20 beacon nodes, which resulted in CLPSO being 80.478% accurate, and PSO 61.48% accurate. The simulation results show that the PSO based localization is faster and CLPSO is more accurate.

Wireless sensor network (WSN) refers to a group of spatially dispersed and dedicated sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at a central location. Sensor Localization is a fundamental challenge in WSN. In this paper localization is modeled as a multi dimensional optimization problem. A comparison study of energy of processing and transmission in a wireless node is done, main inference made is that transmission process consumes more than processing. An energy efficient distributed localization technique is proposed. Distributive localization is addressed using swarm techniques Particle Swarm Optimization (PSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) because of their quick convergence to quality solutions. The performances of both algorithms are studied. The accuracy of both algorithms is analyzed using parameters such as number of nodes localized, computational time and localization error. A simulation was conducted for 100 target nodes and 20 beacon nodes, the results show that the PSO based localization is faster and CLPSO is more accurate.

Mobile ad hoc networks [MANET] are typically characterized by high mobility and frequent link failures that result in low throughput and high end-to-end delay. Present approaches to multipath routing make use of pre-computed routes determined during route discovery. All the paths are maintained by means of periodic update packets unicast along each path. In existing method best path is determined and maintained only with signal strength of disjoint paths. Signal strength between nodes is only the mobility prediction factor, which does not address the durability and stability of paths. Residual energy of nodes determines stability of path contains those nodes. Also does not consider the consistency of node through the previous behaves. This paper provides a design and a simulation frame work for measuring a Decision Value metric for mobility prediction of each alternate paths in MANET. Here a Periodic update packets measure Decision Value metric [DVM] and route maintenance is possible by means of the Signal strength between nodes, Residual energy and Consistency of each hop along the alternate paths, helps protocol to select the best scalable paths.

Water is an important natural resource which needs constant quality monitoring for ensuring its safe use. This paper introduces a river water quality monitoring system based on wireless sensor network which helps in continuous and remote monitoring of the water quality data in India. The wireless sensor node in the system is designed for monitoring the pH of water, which is one of the main parameters that affect the quality of water. The proposed sensor node design mainly comprises of a signal conditioning module, processing module, wireless communication module and the power module. The sensed pH value will be wirelessly transmitted to the base station using Zigbee communication after the required signal conditioning and processing techniques. The circuit for the sensor node is designed, simulated and the hardware prototype is developed using the appropriate components which minimize the power requirement of the system and provides a cost effective platform for monitoring water quality.

This paper presents a novel methodology for optimal placement of Distributed Generation (DG) in an Optimal Power Flow (OPF) based wholesale electricity market. DG is placed in real time wholesale electricity market. The problem of optimal placement including size is formulated for two different objectives, namely, fuel cost reduction and to provide voltage stability at distribution level. DG reduces the cost of electricity to the costumer, relieve network congestion and provide environmental friendly energy close to load centers. The candidate locations for DG placement are identified on the basis of locational marginal price (LMP). OPF is widely used for both the operation and planning of a power system. The key feature of standardization of restructured power market like Standard Market Design (SMD) is the LMP scheme. OPF problem by placing DG in Deregulated Environment is solved using Genetic Algorithm (GA). The proposed methodology is tested with IEEE 30 bus test system.

The smart grid is a new technology that adds efficiency to the electrical grid system. The smart distribution grid architecture proposed in this research work solves major problems faced by the Indian electrical grid such as wastage of energy by the careless usage of consumers, poor power theft and line fault detection method, and manual billing system. The intelligent devices that are placed in different parts of the distribution electrical grid together with the intelligent controlling system make the electrical grid smart.

Illicit and spurious alcohol consumption is leading to numerous deaths in rural India. The aim of this paper is to reduce the death due to the consumption of spurious alcohol by reducing the production of spurious alcohol. A Vehicular Ad- Hoc Sensor Network, MovingNet, is used to detect the production of spurious alcohol. Multiple sensors capable to detect the presence of methanol content or diazepam in a wide geographical area, is incorporated on the available public transport system that traverse through the rural areas of India, where high rate of spurious alcohol production is observed. The data received from the wireless sensors will be transmitted using the delay tolerant, public transport vehicular ad-hoc network, and analyzed at the central data management center. The results of the data analysis will provide the details of geographic information, the amount of presence of methanol content or diazepam, and the warning degree. This will be sent to the excise department which will help them to locate the position and stop the production of spurious alcohol. Thus the implementation of MovingNet will reduce the production of spurious alcohol and contributes the reduction in hazards due to the consumption of spurious alcohol. MovingNet is a cost effective solution since it uses a very few sensors and the available public transport system for data collection and transmission.

Recent years have shown a worldwide increase in terrorist bombings. Continuous monitoring for the presence of explosives in public places can improve security of the public and infrastructure. The objective of this research work is to reduce, control, and warn about the forthcoming terrorist activity by precise and quick detection of explosives. This paper proposes a wide area monitoring system using a multi phase wireless sensor network design. WReMADE uses multiple wireless sensor nodes integrated with different types of sensors to identify the explosives. Based on diverse orthogonal techniques, the system collects data from the sensing nodes, dynamically aggregates the data and forward to the sink node for further analysis. A mobile node has been introduced to further confirm the suspected objects, thus offering an enhanced target tracking mechanism that reduces number of false alarms. W-ReMADE provides an effective warning mechanism for security threats in public places so that immediate action can be taken against bomb threats.
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Wireless Sensor Networks (WSN) are networks of low cost nodes with minimal power consumption, processing capabilities and maintenance, that can be used for wide area environmental monitoring. This paper discusses the main innovations, challenges, solutions and deployment experiences in designing a Lightweight Management Framework (LMF) for a real-time, 24/7 operational, heterogeneous network. The network must reliably deliver data continuously from a set of deep earth probe sensors in a remote hilly rainforest area to a data management, analysis, and visualization center at the University campus hundreds of miles away. This framework provides the ability to incorporate different heterogeneous networks such as 802.15.4, 802.11b/g, VSAT, GPRS, GSM, Internet and also proprietary wireless sensor network and hardware architectures. It also handles various network failures, data corruption, packet loss, and congestion problems. The data is analyzed to determine the factor of safety of the landslide prone area using landslide simulation software, stream data in real-time to the internet, and give automatic warnings. The architecture has been implemented in a real-time wireless sensor network deployed in the Western Ghats of Kerala, India to detect landslides. The architecture is operational in the deployment site since February 2008 and was used to issue landslide warnings during the July 2009 monsoon.

Rainfall induced landslides are a common phenomena in the Western Ghat region of Southern India and result in numerous fatalities and damage to property. In order to collect the most relevant and useful data, at the&nbsp;time&nbsp;it is most needed, a&nbsp;wireless&nbsp;sensor&nbsp;network&nbsp;is being used for&nbsp;landslide&nbsp;monitoring. The advantage it gives to&nbsp;landslide&nbsp;monitoringis that it is an inexpensive and reliable way to communicate rapidly over a long distance and inhospitable terrains, collect data in&nbsp;real-time, and alter the data collection rate remotely to suit current environmental conditions. We have implemented a&nbsp;real&nbsp;time&nbsp;landslide&nbsp;monitoring&nbsp;system over a seven acre active complex&nbsp;landslide&nbsp;site. An array of geological sensors (piezometers, tiltmeters, strain gauges, rain gauges, dielectric moisture sensors, geophones) has already been deployed and the data is being automatically collected and forwarded via the&nbsp;wireless&nbsp;sensor&nbsp;network. The geotechnical data is then transferred over 300 km via a satellite link to a remote&nbsp;monitoring&nbsp;station for further analysis. This will give us a better understanding of landslides in this region and prevent the loss of human life.

Wireless sensor networks are one of the emerging areas which have equipped scientists with the capability of developing real-time monitoring systems. This paper discusses the development of a wireless sensor network(WSN) to detect landslides, which includes the design, development and implementation of a WSN for real time monitoring, the development of the algorithms needed that will enable efficient data collection and data aggregation, and the network requirements of the deployed landslide detection system. The actual deployment of the testbed is in the Idukki district of the Southern state of Kerala, India, a region known for its heavy rainfall, steep slopes, and frequent landslides.

The installation or deployment of a wireless sensor network (WSN) in a real world application is prone to innumerable failures such as software or hardware malfunctioning, environmental hazards, radio interference, battery exhaustion, etc. In a safety critical application such as landslide prediction, fault tolerant approaches have to be followed to ensure the availability of sensor data at the analysis station during a critical situation. We propose a fault tolerant and energy efficient clustering approach which organizes the whole network into smaller cluster and subcluster groups enabling a considerable reduction of communication and processing overhead. Subcluster formation also gives the possibility to skillfully deal with sensor nodes, node leader, and cluster head failures. We also propose a fault tolerant approach that uses a matrix based error approximation method for providing the approximate sensor data of the failed node. The approximate code prediction takes into consideration various geological aspects of the problem.

In a smart distribution power grid, cost efficient and reliable communication architecture plays a crucial role in achieving complete functionality. There are different sets of Quality of Services (QoS) requirements for different data packets transmitting inside the microgrid (a regionally limited smart distribution grid), making it challenging to derive optimal communication architecture. The objective of this research work is to determine the optimal communication technologies for each data packet based on its QoS requirement. In this paper, we have proposed an architecture for a smart distribution power grid with Cyber Physical System enabled microgrids, which accommodate almost all functional requirements of a smart distribution power grid. For easy transition towards optimal communication architecture, we have presented a six-tier communication topology, which is derived from the architecture for a smart distribution power grid. The optimization formulations for each packet structure presented in this paper minimize the overall cost and consider the QoS requirements for each packet. Based on the simulation results, we have made recommendations for optimal communication technologies for each packet and thereby developed a heterogeneous communication architecture for a microgrid.

Fishermen at sea lack proper localization and tracking systems leading to increased loss of life at sea due to disasters, engine failure, and collision with ships. To reduce the impact of such scenarios we need an efficient localization and tracking algorithm for approximate localization of fishing vessels in a spatio – temporal domain. In this work, we have analyzed few existing algorithms for localization of mobile sensor nodes and based on these results, an Enhanced Chord Based Localization Algorithm (ECLA) has been designed and developed. The proposed algorithm is implemented and extensively tested on the basis of different performance parameters such as mobility, localization accuracy, execution time etc. The experimental results clearly show that the proposed algorithm has better localization accuracy compared to the existing localization algorithms. The accuracy of the proposed ECLA algorithm is 26.5% better than that of Monte Carlo Boxed (MCB) localization scheme.

In a maritime environment, affordable long range communication network for fishing vessels are highly necessary for safety at sea and to communicate to shore and back to the fishing vessels. The existing communication architecture faces major challenges in achieving seamless connectivity due to the mobility of fishing vessels, lack of backbone infrastructure, propagation effects, and fault tolerance. In this work, we explored the capability of Delay Tolerant Networks (DTN) for providing better connectivity under the above mentioned parameters. Existing DTN protocols such as Epidemic, Spray and Wait and MaxProp protocols were studied and analyzed for maritime scenario. These protocols were simulated in Opportunistic Networking Environment (ONE) simulator and analyzed with respect to node density, node mobility, and intermittent connectivity. The results show that Epidemic protocol has moderate average latency, whereas Spray and Wait protocol and MaxProp has better data delivery rate with lesser average latency.

In this paper we present a wireless wearable body area system for locating, tracking and monitoring emergency responders in harsh and remote environments. Tracking an emergency responder and monitoring their vital signs using various medical sensors is important in supporting the safety of the emergency responder. This work is the preliminary step towards the development of a collaborative real-time tracking and monitoring system for emergency responders. In this paper, we propose a design of a wrist worn wireless wearable body sensor device for localizing, tracking and monitoring an emergency responder. Any change in the physiological parameters like blood oxygen level, blood pressure and pulse rate of the emergency responder can be easily sensed and tracked, and could be used to provide a warning when a critical event is detected. This system uses an efficient iterative localization scheme for locating the emergency responder. The system could be used to send early warning alerts, route proper medical supplies to the area required, and for communication between the responders.

The Electrocardiogram (ECG) is a graphical recording of the electrical signals generated by the heart. The signals are generated when the cardiac muscles depolarize in response to electrical impulses generated by the pacemaker. In this work, we propose an efficient method to monitor and classify the ECG signals. The initial task carried out was to eliminate the noise, which involved extracting the required cardiac components by rejecting the background noise. The second task was to perform R peak detection, which was achieved by using the Windowed Short Time Fourier Transform (STFT). The Heart Rate Variability (HRV) was also found by calculating the difference between two simultaneous R-Peaks. The simulations were carried out in the MATLAB environment. The experiments were carried out using data from the MIT-BIH Database. This paper proposes an algorithm to monitor cardiac atrial fibrillation, which is an essential precursor to myocardial infarction.

We present an intelligent data management framework that can facilitate development of highly scalable and mobile healthcare applications for remote monitoring of patients. This is achieved through the use of a global log data abstraction that leverages the storage and processing capabilities of the edge devices and the cloud in a seamless manner. In existing log based storage systems, data is read as fixed size chunks from the cloud to enhance performance. However, in healthcare applications, where the data access pattern of the end users differ widely, this approach leads to unnecessary storage and cost overheads. To overcome these, we propose dynamic log chunking. The experimental results, comparing existing fixed chunking against the H-Plane model, show 13 %–19 % savings in network bandwidth as well as cost while fetching the data from the cloud.

Ubiquitous Computing with Context Awareness is emerging as a significant technology which is capable of supporting a wide variety of real world applications such as health care, environmental monitoring, security, etc. Most of the existing Context aware frameworks developed are single-application oriented. The key focus of our research work is to bring in multiple application support using single context aware framework. The proposed Ubiquitous Multi-Context Model (UMM) contains a new module “Context Categorizer” for spanning multiple real world applications. The designed model support non redundant information capturing and appropriate data sharing among multiple applications, by utilizing the potentials of wireless sensor networks. The implementation of the proposed model considers two relevant applications, health care and crowd behavior estimation, which are gaining attention nowadays.

Publication Type: Patent

Year of Publication

Publication Type

Title

2014

Patent

Dr. Maneesha V. Ramesh, “Network-Based System for Predicting Landslides and Providing Early Warnings”, U.S. Patent US 13/168,3572014.[Abstract]

A wireless node for monitoring landslide conditions has at least one tubular probe body deployed in a borehole in a landslide prone area and anchored to rock below soil, multiple sensors carried by and deployed within and or outside of the tubular probe body for measuring geologic motion, hydrologic saturation and pressure at three or more levels of soil above the rock, a data acquisition board in communication with the sensors carried by and or deployed within or outside of the probe body, and a wireless transceiver in communication with the data acquisition board and accessible to a local area wireless network (LAWN). Geologic and hydrologic data of layers of soil above the anchor rock is from the sensors deployed on or near the probe body, the data qualified against threshold readings to provide graduating levels of alerts culminating in a warning of a landslide.

According to World Health Organization, worldwide, every year, more than 12 million people are killed in accidents and more than 500 million people are injured. In this research work, we have designed a context aware wireless sensor system to detect and locate road accidents in real-time. Context acquisition is performed using onboard sensors such as accelerometer, gyroscope, flex sensor and sensors from Smartphone such as accelerometer, microphone, GPS etc. A learning algorithm is proposed to perform context modeling, inference, and context-based action initiation. Participatory sensing techniques are integrated with the proposed system to ensure system enhancement and reduce false alarms.

In this paper, we present a real time remote triggered laboratory which has multi-set, multi-group of wireless sensor network experimental setup which is envisioned to provide a practical experience of designing and implementing wireless sensor networks' algorithms in both indoor and outdoor conditions. The architecture provides a remote code editing mechanism using deluge protocol that offers the user a flexible environment for the experimentation. Central and local authentication agents serve a two level security mechanism which makes the system robust to security threats. The lab is accessible for all the students in the world through internet and it will provide an intuitive web-based interface, where registered users can access the code and do code editing.